Which of these is not a consequence of ignoring autocorrelation if it is present?
A) The coefficient estimates derived using OLS are inefficient
B) Standard error estimates are inappropriate
C) The coefficient estimates derived using OLS are biased
D) The coefficient estimates derived using OLS are not the best linear unbiased estimators

Question

Quizplus · Accepted Answer

Ignoring autocorrelation when it is present in a regression model does not bias the coefficient estimates derived using Ordinary Least Squares (OLS); rather, it affects the efficiency of these estimates and the appropriateness of the standard error estimates, making the OLS estimates not the best linear unbiased estimators (BLUE).

Which of These Is Not a Consequence of Ignoring Autocorrelation